Data-Driven Cooperative Adaptive Cruise Control of Buses on the Exclusive Bus Lane of the Lincoln Tunnel Corridor
Proceedings of the TRB Annual Meeting
The exclusive bus lane (XBL) is one of the most popular bus transit systems in US. The Lincoln Tunnel utilizes an XBL through the tunnel in the AM peak period. This paper proposes a novel data-driven cooperative adaptive cruise control (CACC) algorithm for connected and autonomous buses. Different from existing model-based CACC algorithms, the proposed approach employs the idea of adaptive dynamic programming (ADP), which does not rely on the accurate knowledge of bus dynamics. A distributed cruise controller is learned by online headway, velocity, acceleration data collected from system trajectories. The convergence of the proposed algorithm and the stability of the closed-loop system are rigorously analyzed. The effectiveness of the proposed approach is also demonstrated by Paramics microscopic traffic simulations. Simulation results show that the travel times in the autonomous exclusive bus lanes are close to the present day travel times even when the traffic demand is increased by 30%.
Gao, Weinan, Zhong-Ping Jiang, Kaan Ozbay, Jingqin Gao.
"Data-Driven Cooperative Adaptive Cruise Control of Buses on the Exclusive Bus Lane of the Lincoln Tunnel Corridor."
Proceedings of the TRB Annual Meeting.